Data Scientist, Computational & Mechanistic (onsite)
About The Position
Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue exceeding $40 billion. Our mission is to enable our customers to make the world healthier, cleaner, and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, improving patient diagnostics and therapies, or increasing productivity in their laboratories, we are here to support them. We are seeking a highly motivated Data Scientist with strong hands-on expertise in machine learning and deep learning (ML/DL), as well as mechanistic modeling, to join our interdisciplinary team. In this role, you will collaborate closely with experts in cell culture, multi-omics, and data science to develop and apply advanced hybrid modeling approaches that accelerate new cell culture product development and support media development services. This position offers the opportunity to work in a highly collaborative, innovation-driven environment while contributing to Thermo Fisher Scientific’s mission to enable a healthier, cleaner, and safer world.
Requirements
- Ph.D. in Computational Biology, Bioinformatics, Mathematics, Data Science, or related field.
- M.S. with 3+ years of industry or academic experience in mechanistic modeling, machine learning, or bioproduction applications.
- Experience in stoichiometric modelling of cell metabolism including metabolic flux analysis (MFA), flux balance analysis (FBA) etc.
- Demonstrated experience in mechanistic modeling, including development and application of first-principles models such as ODE/PDE-based, kinetic, mass-balance, or systems biology models.
- Proficiency in machine learning methods such as regression, classification, neural networks, ensemble methods, or Gaussian processes.
- Hands-on experience in building hybrid (mechanistic + ML) models and applying them to complex, data-driven problems such as bioprocess optimization, systems biology, digital twins, and process control.
- Experience working with high-dimensional and time-series experimental data.
- Strong programming skills in Python, with proficiency in relevant ML and modeling libraries such as scikit-learn, TensorFlow, and PyTorch.
- Proven experience in building and deploying interactive dashboards in Python, ideally using Dash or similar frameworks.
- Experience working with cloud-based data platforms (e.g. Databricks) and proficiency with version control systems such as GitHub.
- Excellent verbal and written communication skills, with demonstrated ability to present complex analytical findings to diverse scientific and business stakeholders.
- Ability to manage multiple priorities simultaneously and deliver high-quality results with minimal supervision.
- Demonstrated ability to translate complex modeling results into actionable insights for scientific, engineering, or business stakeholders.
- Strong cross-functional collaboration skills, with experience working effectively across multidisciplinary teams.
Nice To Haves
- Knowledge in molecular and cellular biology.
- Experience in cell culture media development and/or bioproduction workflows.
Responsibilities
- Develop hybrid modeling approaches that integrate mechanistic models with machine learning to optimize cell culture media, improve media design success rates, and accelerate development timelines.
- Build intuitive, user-friendly interfaces for implementing the hybrid models and deploy web applications on AWS EC2.
- Collaborate with cross-functional teams to understand scientific and operational requirements and develop modeling solutions that optimize various aspects of the bioproduction workflow.
- Communicate results and insights effectively to interdisciplinary project teams and stakeholders.
- Provide training and mentorship to R&D scientists and junior data scientists, supporting skill development and adoption of modeling tools.
- Contribute to grant proposals and other funding initiatives to support new data science and modeling capabilities.
Benefits
- A choice of national medical and dental plans, and a national vision plan, including health incentive programs
- Employee assistance and family support programs, including commuter benefits and tuition reimbursement
- At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
- Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
- Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
